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Paircoil2: improved prediction of coiled coils from sequence.
Open accessAbstract
Summary: We introduce Paircoil2, a new version of the Paircoil program, which uses pairwise residue probabilities to detect coiled–coil motifs in protein sequence data. Paircoil2 achieves 98% sensitivity and 97% specificity on known coiled coils in leave-family-out cross-validation. It also shows superior performance compared with published methods in tests on proteins of known structure. Availability: Paircoil2 is freely available as a web application and for download at Contact: keating@mit.edu; bab@mit.edu Supplementary information: Available at Bioinformatics online and at the Paircoil website.
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“A new coiled-coil database of 1279 dimers and 333 trimers is derived from three sources: the Paircoil2 training set [9], coiled coils detected in the PDB using SOCKET, and new coiled-coil families described in the literature.”
From Multicoil2: Predicting Coiled Coils and Their Oligomerization States from Sequence in the Twilight Zone (2011) · cites this paper as [9]
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Metadata
- Authors
- McDonnell, A. V., Jiang, T., Keating, A. E., & Berger, B.
- Affiliations
- MIT Computer Science and Artificial Intelligence Laboratory (US)
- Massachusetts Institute of Technology (US)
- Corresponding author
- Keating, A. E.
- Berger, B.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-11-29
- Volume
- 22
- Issue
- 3
- Pages
- 356-358
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2117709367
- Semantic Scholar
- 67080275c2f525632c88cf8bec8612acc6963372
- Cited by
- 424
- References
- 22
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 16 · 2023: 15 · 2022: 18 · 2021: 27 · 2020: 19 · 2019: 25 · 2018: 19 · 2017: 27 · 2016: 25 · 2015: 22 · 2014: 25 · 2013: 22 · 2012: 41
- FWCI
- 4.64
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation (0347203, CAREER)
- National Institutes of Health
- National Institute of General Medical Sciences (GM67681, R01GM067681)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- coiled-coil domain, protein sequence analysis, web application, structure prediction
- MeSH terms
- Algorithms, Amino Acid Sequence, Computer Simulation, Models, Chemical, Models, Molecular, Molecular Sequence Data, Sensitivity and Specificity, Software, Reproducibility of Results, Sequence Analysis, Protein
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